Video data communications can have high data error rates, particularly in mobile applications where carrier signals tend to randomly fade for several seconds due to transmitter/receiver motion acting in conjunction with signal path physical obstructions. During periods of such high data error rates, video quality can be severely degraded due to a reduction in data throughput over a finite transmission time period. Such throughput reduction results when normal data transmission time is consumed by error-correction processing activities, such as repeatedly re-transmitting a damaged data packet or processing data with time-consuming error-correction algorithms at both the transmitter and receiver ends of a communications system.
To alleviate time lost to such error-correction, various data compression techniques can be employed to reduce the size of transmitted data packets. Such techniques take advantage of the fact that smaller data packets result in smaller transmission time slots being required for re-transmission of damaged data blocks and/or enable the use of less sophisticated, and thus less time consuming, error-correction algorithms. One such data reduction technique that has particular application to video images relies on the fact that the human eye is foveated. Foveation is characterized by exponentially decreasing image resolution away from the focal point of the eye resulting in being able to see the fine details only in the area of focus.
Thus, due to this non-uniform resolution processing of the human eye, high frequency data components can be removed from areas of lesser importance without a corresponding loss of visual quality. This high frequency elimination provides an attendant reduction in the quantity of data needed for the transmission of a quality video image. Such foveated video data compression techniques have been successfully used at very low bit rates for such data communications. See S. Lee et al, “Foveated Video Quality Assessment”, IEEE Trans. Multimedia and S. Lee, et al, “Foveated video compression with optimal rate control”, IEEE Trans. Image Processing, both submitted, but not yet published.
In another application using foveation, U.S. Pat. No. 4,692,806 to Anderson, et al, teaches that data transmissions of a “busy” video image can be improved by performing successive processing passes over an image. A first pass captures a data block for an overall general image area, and then successive passes capture a finer area of detail or selective images of importance. Control of the “selected area” is accomplished by pointing/aiming a video camera to the points of importance based on feedback from a remote viewing screen. As is known in the art, there are many techniques for such camera manipulation to a targeted area of an image, such as using eye-tracking devices, a computer mouse, and/or a joystick. Once a targeted area is selected, detailed data processing is made only on the selected area.
However, a significant disadvantage of this technique is that it does not correct for a data transmission exhibiting a high bit error rate, such as those characteristic of the mobile applications cited above. Although such high data error rates will negatively impact both the selected area and the background area equally, the lack of extra error correction/resilience for the important “selected area” leads to significant perceptual degradation in the received video image.